Multi-input cascade micro-ring structure optical differentiator and application method thereof

Abstract

The invention discloses a multi-input cascade micro-ring structure optical differentiator and an application method thereof, and relates to the technical field of integrated optical computing, and the multi-input cascade micro-ring structure optical differentiator comprises a plurality of micro-ring resonators which are connected in series; each micro-ring resonator is provided with an independent input port, and the plurality of micro-ring resonators connected in series share one output port; different input ports are used for activating optical differential responses of corresponding orders respectively; a reversible phase change material is deposited on each micro-ring resonator; the reversible phase change material is used for realizing programmable state switching. According to the invention, flexible regulation and control of differential orders and response characteristics can be realized.

Description

Technical Field

[0001] The present application relates to the field of integrated optical computing technology, and in particular to a multi-input cascade micro-ring structure optical differentiator and an application method thereof. Background Art

[0002] Currently, optical differentiators, as important functional devices for high-speed optical computing and edge image processing, have a certain theoretical and experimental basis, especially showing good application prospects in silicon-based microring resonator structures. However, the existing technology still has the following prominent problems:

[0003] 1. The differential function is fixed and lacks adjustability.

[0004] Most differentiators based on single microrings only support first-order or specific forms of differential operations and cannot flexibly adjust the differential order or response strength according to actual applications, limiting their applicability in complex signal processing scenarios.

[0005] 2. The structural expansion method is simple and the device redundancy is high.

[0006] Although some studies have attempted to achieve high-order differentials by connecting multiple microrings in series or in parallel, the lack of effective geometric structure optimization has led to device size expansion and decreased coupling efficiency, while also making it difficult to achieve structural multiplexing and parameter tuning.

[0007] 3. The control mechanism is single and relies on external thermal control or electrical control solutions.

[0008] Current control methods mostly rely on heating or electrical control solutions, which have slow response speed, high power consumption, limited control accuracy, and are difficult to deploy on a large scale in systems with high integration density.

[0009] 4. The material design has poor versatility and functional areas cannot be locally programmable.

[0010] Most devices use traditional silicon materials or uniform phase change layers, and do not introduce patterning or structural partitioning in the design of material functional areas, resulting in obvious deficiencies in the devices' control accuracy, reusability, and reconfigurability.

[0011] Therefore, how to achieve flexible regulation of the differential order and response characteristics has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0012] The purpose of this application is to provide a multi-input cascade micro-ring structure optical differentiator and its application method, which can realize flexible regulation of differential order and response characteristics.

[0013] To achieve the above objectives, this application provides the following solutions:

[0014] In a first aspect, the present application provides a multi-input cascade micro-ring structure optical differentiator, the multi-input cascade micro-ring structure optical differentiator comprising:

[0015] Several microring resonators connected in series.

[0016] Each of the microring resonators is provided with an independent input port, and a plurality of microring resonators connected in series share one output port; different input ports are used to respectively activate optical differential responses of corresponding orders.

[0017] A reversible phase change material is deposited on each of the microring resonators; the reversible phase change material is used to realize programmable state switching.

[0018] Optionally, the deposition area of ​​the reversible phase change material is the inner side of the microring resonator.

[0019] In a second aspect, the present application provides an application method of a multi-input cascade micro-ring structure optical differentiator, the application method of the multi-input cascade micro-ring structure optical differentiator comprising:

[0020] Convert the input color image to a grayscale image.

[0021] The grayscale image is binarized to obtain a binarized image.

[0022] The binarized image is converted into a time series signal to obtain a one-dimensional time series.

[0023] Performing analog signal conversion on the one-dimensional time series to obtain an analog electrical signal.

[0024] The analog electrical signal is subjected to optical signal modulation conversion to obtain an intensity modulated optical signal.

[0025] The intensity modulated optical signal is input into a multi-input cascaded phase-change micro-ring structure optical differentiator for differentiation to obtain a differential output optical signal; the multi-input cascaded phase-change micro-ring structure optical differentiator is the optical differentiator described above.

[0026] The differential output optical signal is photoelectrically detected to obtain a converted electrical signal, and the converted electrical signal is sampled and data is rearranged to obtain a two-dimensional edge image.

[0027] Optionally, the grayscale image is calculated as follows:

[0028] I gray (x,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y);

[0029] Among them, I gray(x,y) is a grayscale image; R(x,y) is the intensity of the red component of the image at the pixel coordinate (x,y); G(x,y) is the intensity of the green component of the image at the pixel coordinate (x,y); B(x,y) is the intensity of the blue component of the image at the pixel coordinate (x,y).

[0030] Optionally, the expression for the binarization process is:

[0031]

[0032] Among them, I binary (x, y) is the image after binarization processing; I gray (x,y) is a grayscale image; K is a fixed threshold.

[0033] Optionally, the expression for the time series signal conversion is:

[0034] S(t)={I binary {x1,y1),I binary (x2,y2),...,I binary (x M ,y L )};

[0035] Where S(t) is the pixel value sequence obtained by scanning row by row; M and L are the number of rows and columns of the image respectively; I binary (x M ,y L ) is the image after binarization processing in the Mth row and Lth column.

[0036] Optionally, the expression for analog signal conversion is:

[0037]

[0038] Among them, V analog (t) is the analog electrical signal; S(t) is the pixel value sequence obtained by scanning line by line; V max is the maximum voltage of the analog signal.

[0039] Optionally, the expression for the optical signal modulation conversion is:

[0040]

[0041] Among them, I out is the intensity modulated optical signal; I in is the input light intensity; V π The voltage required to achieve π phase shift; V analog (t) is the analog electrical signal.

[0042] Optionally, the differential expression is:

[0043] I diff (t) = T N I out ;

[0044]

[0045] Among them, I diff (t) is the differential output optical signal; I out is the intensity modulated optical signal; T N is the power transfer function of N-cascaded all-pass micro-rings; a is the loop loss coefficient; t is the transmission coefficient; is the ring phase shift of the microring resonator, which indicates the phase change of the light field when it propagates in the ring; T is the power of the microring resonator; N is the number of microring resonators.

[0046] Optionally, the expression for obtaining the two-dimensional edge image is:

[0047] I edge (x,y)=reshape(I diff (t),M,L);

[0048] Among them, I edge (x,y) is a two-dimensional edge image; I diff (t) is the differential output light signal; M and L are the number of rows and columns of the image, respectively.

[0049] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0050] This application provides a multi-input cascaded microring optical differentiator and its application method. The multi-input cascaded microring optical differentiator comprises: a plurality of microring resonators connected in series; each microring resonator has an independent input port, and the plurality of microring resonators connected in series share a single output port; different input ports are used to activate optical differential responses of corresponding orders; and each microring resonator is deposited with a reversible phase-change material; the reversible phase-change material is used to achieve programmable state switching. In this application, each cascaded microring has an independent input port, and by depositing the reversible phase-change material, the device possesses selectable, programmable, and combinable fractional-order differential functionality. This structure, previously unseen in programmable photonic devices such as field programmable ring arrays, fills a structural gap in differential control. This application designs material-controllable regions within each microring, independently controlling the response characteristics of different microrings through state switching, supporting multi-port and multi-order joint regulation. This partitioned control approach improves the functional reconfiguration freedom and response speed of the device, effectively overcoming the limitations of traditional monolithic material control, which suffers from slow response and single functionality. The outputs of several micro-rings are unified and converged to a common output port, which simplifies the optical path design and signal processing interface; compared with the structure of using multiple ports to read out the results of different orders of differentials in the prior art, the design of this application has higher system integration efficiency and implementation potential, and is suitable for industrial-grade packaging. Through innovations in structure and input port design, this application can support first-order, second-order, third-order and fractional-order differential functions, and through simultaneous activation of multiple input ports, order superposition or combination operations can be achieved, providing richer and more customizable differential operator outputs for complex signal processing. In addition, this application can dynamically call and switch different differential operators by regulating the combination of material state and input ports, thereby realizing multi-scale, adjustable intensity edge extraction in image processing. This structure supports flexible control of image response characteristics, is suitable for a variety of image recognition, detection and visual perception scenarios, and can improve the accuracy of edge processing and system adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 A schematic structural diagram of a multi-input cascaded micro-ring structure optical differentiator provided in one embodiment of the present application.

[0053] Figure 2 A schematic structural diagram of a reconfigurable dual-cascade microring optical differentiator provided in one embodiment of the present application.

[0054] Figure 3 This is a flow chart of the algorithm of a reconfigurable dual-cascade microring optical differentiator provided in one embodiment of the present application.

[0055] Figure 4 A flowchart of an application method of a multi-input cascaded micro-ring structure optical differentiator provided in one embodiment of the present application.

[0056] Figure 5 This is a flowchart of an image edge algorithm based on a micro-ring optical differentiator provided in one embodiment of the present application.

[0057] Figure 6 Schematic diagram of an input image and a grayscale image of an edge extraction system provided in one embodiment of the present application.

[0058] Figure 7 A schematic diagram of converting a one-dimensional time series into an analog signal according to an embodiment of the present application.

[0059] Figure 8 A schematic diagram of a signal after MZM modulation provided in an embodiment of the present application.

[0060] Figure 9 A schematic diagram of a differentiated output signal after passing through a micro-ring according to an embodiment of the present application.

[0061] Figure 10 A schematic diagram of single micro-ring output restoration provided in one embodiment of the present application.

[0062] Figure 11 A schematic diagram of cascaded micro-ring output restoration provided in one embodiment of the present application.

[0063] Figure 12 A schematic diagram of adjusting the GST-SL6 loss edge extraction provided in an embodiment of the present application.

[0064] Figure 13 Schematic diagram of a reconfigurable three-cascade microring optical differentiator provided in one embodiment of the present application. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0066] While existing silicon-based microring resonators offer advantages such as compact structure, ease of integration, and high quality factor, promising broad applications in integrated optical computing, the inherent lack of dynamic control capabilities of silicon makes it difficult to meet the demands of real-time, flexible optical differential operations, limiting their application in high-speed signal processing and intelligent computing. Furthermore, some existing tunable optical microring structures suffer from limited response bandwidth, single functionality, and complex control mechanisms, making it difficult to balance the system's high-order differential computing capabilities, power consumption control, and structural compatibility.

[0067] To address the above problems, this application provides a multi-input cascaded micro-ring structure optical differentiator and its application method to solve the following key technical difficulties:

[0068] A reasonable geometric arrangement of cascaded microrings is proposed to achieve flexible configuration of multi-order differential functions while maintaining the compactness of the device; that is, a compact cascade structure is constructed based on a single microring, and the computational function of the differential device is expanded through a reasonable geometric arrangement (such as microring radius, differentiated configuration of optical coupling intensity, etc.).

[0069] By setting up material control areas on the cascaded microring structure and combining it with the control of the material state, the dynamic configuration of the functional state of each microring is achieved, thereby giving the device programmable differential response capability; that is, by setting up material areas with controllable characteristics on the microring structure, through patterned design and functional differentiation layout, the optical response states of different microring segments can be finely controlled, thereby giving the system programmable differential order capability.

[0070] Combined with the independent input ports of each microring, differential channels of different orders can be flexibly activated, giving the entire system structural-level reconstruction capabilities and programmable input and output control capabilities; that is, each microring has an independent input port, combined with the material state regulation mechanism, so that different inputs can activate differential responses of different orders respectively, realizing functional reconstruction at the structural level.

[0071] This multi-order, reconfigurable differential structure is used to adjust the edge response to different levels of grayscale changes in image processing. Different orders of differential paths can be called according to specific application requirements to achieve multi-scale, customizable image edge extraction functions; that is, it is ultimately possible to achieve an optical differential calculation unit with a simple structure, sensitive response, high integration and programmable differential function, which is suitable for application scenarios such as image processing, edge detection, and high-speed signal differentiation.

[0072] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0073] like Figure 1As shown, this application proposes a multi-input cascaded microring optical differentiator. Based on a silicon-based integrated optical waveguide platform, it employs a cascaded microring resonator structure and combines it with a programmable and patterned phase-change material deposition design to achieve flexible control of the differential order and response characteristics. This structure has applications in optical edge detection, high-speed signal processing, and photonic computing.

[0074] The multi-input cascade micro-ring structure optical differentiator comprises:

[0075] Several microring resonators connected in series.

[0076] Each of the microring resonators is provided with an independent input port, and a plurality of microring resonators connected in series share one output port; different input ports are used to respectively activate optical differential responses of corresponding orders.

[0077] A reversible phase change material is deposited on each of the microring resonators; the reversible phase change material is used to realize programmable state switching.

[0078] The deposition area of ​​the reversible phase change material is the inner side of the microring resonator.

[0079] This application, based on a single microring structure, connects multiple size-controllable microring resonators in series to form a cascade structure with a spatially sequential coupling relationship. Each microring can be designed with a different ring diameter, coupling region length, or waveguide spacing, thereby achieving: combining and controlling multi-order differential responses; adjusting the coupling strength and phase response of different frequency components; and constructing frequency response characteristics similar to differential transfer functions under specific coupling structures.

[0080] The power transfer function of the N-cascaded all-pass microring is as follows:

[0081]

[0082] Among them, T N is the power transfer function of N-cascaded all-pass micro-rings; a is the loop loss coefficient; t is the transmission coefficient; is the ring phase shift of the microring resonator, which indicates the phase change of the light field when it propagates in the ring; T is the power of the microring resonator; N is the number of microring resonators.

[0083] like Figure 2 As shown, a reconfigurable dual-cascade microring optical differentiator is provided, and the transfer function of the dual-cascade microring is:

[0084]

[0085] Wherein, T2 is the power transfer function of the N-cascaded all-pass microring.

[0086] Using MATLAB simulation software, a reconfigurable dual cascade optical differentiator simulation algorithm is proposed. The algorithm process mainly includes: signal modulation, code control, micro-ring parameter setting, cascade micro-ring configuration, GST-SL6 loss adjustment, differential order comparison, and differential result analysis. The algorithm flow chart is as follows Figure 3 shown.

[0087] By further controlling the material state through the algorithm, the microring's differential order was successfully expanded to 2.5, significantly improving the system's differential capability. This opens up the potential for broader application of microring optical differentiators in more complex signal processing tasks. Furthermore, during laser manipulation of the GST state, the microring can be precisely controlled to enter a critical coupling state, enabling high-precision differential operations under these conditions, further enhancing the system's adjustability and stability.

[0088] Image edge detection is a core technology in computer vision and image processing. Its primary purpose is to identify areas within an image where grayscale or color changes dramatically, thereby extracting object edge information. Traditional edge detection methods, such as the Sobel, Prewitt, and Laplacian operators, are typically based on digital image processing techniques and rely on convolution calculations using discrete filter kernels. However, these methods are limited by computational speed and power consumption, making them difficult to meet the demands of real-time and efficient processing.

[0089] The aforementioned research demonstrated that a reconfigurable microring optical differentiator based on GST-SL6 can perform optical differential operations of varying orders, and its differential performance can be dynamically adjusted by laser-controlled manipulation of the GST-SL6 material state. Based on this, the microring optical differentiator is used to detect image edges in the optical domain, converting image signals into optical signals and performing real-time differential calculations in the optical domain, thereby improving the processing speed and computational efficiency of edge detection.

[0090] Mathematically, edge detection can be expressed as a differential operation on the grayscale distribution of an image. Assuming that the grayscale distribution function of the input image is I(x, y), edge detection usually uses a first-order differential operator to extract gradient information, namely:

[0091]

[0092] Among them, G(x,y) is the gradient amplitude, and are the horizontal and vertical gradient components of the image respectively.

[0093] In traditional digital image processing, this calculation is implemented through discrete difference approximation, such as the Sobel operator:

[0094]

[0095]

[0096] Among them, G x and G y Represents the gradient information of the image in the horizontal and vertical directions respectively; * represents the two-dimensional convolution operation. Finally, the gradient amplitude can be calculated by the following formula:

[0097]

[0098] Edge detection results are usually determined by setting an appropriate threshold to determine whether an edge exists. When the gradient amplitude is greater than a certain threshold, the pixel is considered to belong to the edge area; otherwise, it is considered to be background. Although traditional electrical methods have been widely used in image edge detection, the following problems still exist:

[0099] 1. High computational complexity: For high-definition images, gradient calculation involves a large number of convolution operations, which consumes huge computing resources, especially in high-resolution video processing tasks.

[0100] 2. High power consumption: Traditional image processing relies on digital signal processing or GPU accelerated computing. Under large-scale processing tasks, power consumption becomes an issue that cannot be ignored.

[0101] 3. Limited real-time performance: For ultra-high-speed image streams or THz-level real-time signals, the processing speed of electronic computing cannot meet the high-frequency signal processing requirements.

[0102] In order to solve the above problems, researchers have begun to explore edge detection methods based on optical computing in recent years. Among them, the method based on micro-ring optical differentiator has become an important development direction in the field of optical computing due to its high speed, low power consumption and parallel computing capabilities.

[0103] Based on the analysis of the theoretical model of the micro-ring optical differentiator in the previous article, this embodiment will introduce in detail the image processing process based on the micro-ring optical differentiator. The process mainly includes image pre-processing, optical signal conversion, optical differential operation, and subsequent edge detection and feature extraction. Through this process, the differential characteristics of the micro-ring optical differentiator are used to achieve edge detection of the input image. Figure 4 As shown, a method for applying a multi-input cascade micro-ring structure optical differentiator is provided, and the method for applying the multi-input cascade micro-ring structure optical differentiator includes:

[0104] S1: Convert the input color image to a grayscale image.

[0105] S2: performing binarization processing on the grayscale image to obtain a binarized image.

[0106] S3: Performing time series signal conversion on the binarized image to obtain a one-dimensional time series.

[0107] S4: performing analog signal conversion on the one-dimensional time series to obtain an analog electrical signal.

[0108] S5: Perform optical signal modulation conversion on the analog electrical signal to obtain an intensity modulated optical signal.

[0109] S6: inputting the intensity modulated optical signal into a multi-input cascaded phase-change micro-ring structure optical differentiator for differentiation to obtain a differential output optical signal; the multi-input cascaded phase-change micro-ring structure optical differentiator is the optical differentiator described above.

[0110] S7: Perform photoelectric detection on the differential output light signal to obtain a converted electrical signal, sample the converted electrical signal and rearrange data to obtain a two-dimensional edge image.

[0111] As an optional implementation, in step S1, the input color image I RGB (x,y) needs to be converted to a grayscale image I gray (x,y) so that the subsequent differential operation can directly process the pixel brightness information. The grayscale image is calculated as follows:

[0112] I gray (x,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y) (7);

[0113] Among them, I gray (x,y) is a grayscale image; R(x,y) is the intensity of the red component of the image at the pixel coordinate (x,y); G(x,y) is the intensity of the green component of the image at the pixel coordinate (x,y); B(x,y) is the intensity of the blue component of the image at the pixel coordinate (x,y).

[0114] As an optional implementation, in step S2, the grayscale image is binarized to further enhance edge features. In this embodiment, a fixed threshold K is used for binarization:

[0115]

[0116] Among them, I binary (x, y) is the image after binarization processing; K can be dynamically adjusted according to the Otsu method or other adaptive algorithms to obtain the best image segmentation effect.

[0117] As an optional implementation, in step S3, in order to process the image information in the optical system, it is necessary to convert the discrete grayscale image into a time series signal. Assuming the image size is M×L, the two-dimensional image can be serialized into a one-dimensional time series by expanding it by columns:

[0118] S(t)={I binary (x1,y1),I binary (x2,y2),...,I binary (x M ,y L )} (9);

[0119] Where S(t) is the pixel value sequence obtained by scanning row by row, which provides input for subsequent analog signal conversion; M and L are the number of rows and columns of the image respectively; I binary (x M ,y L ) is the image after binarization processing in the Mth row and Lth column.

[0120] As an optional implementation, in step S4, since optical signal processing mainly processes analog signals, it is necessary to convert discrete digital image data into continuous analog signals. This process usually uses a digital-to-analog converter (DAC). The DAC process is as follows:

[0121]

[0122] Among them, V analog (t) is the analog electrical signal; V max is the maximum voltage of the analog signal.

[0123] The essence of this process is to map discrete digital pixel values ​​to continuous electrical signals to facilitate subsequent optical modulation.

[0124] As an optional implementation, in step S5, the analog electrical signal needs to be converted into an optical signal by the MZM so as to be input into the microring resonator for processing. The transfer function of the MZM is:

[0125]

[0126] Among them, I out is the intensity modulated optical signal; I in is the input light intensity; V π The voltage required to achieve π phase shift; V analog (t) is the analog electrical signal.

[0127] As an optional implementation, in step S6, the analog electrical signal is converted into an intensity modulated optical signal by the MZM and input into a reconfigurable microring optical differentiator, i.e., a multi-input cascaded phase-change microring optical differentiator. The intensity modulated optical signal is differentiated using the power transfer function of an N-cascaded all-pass microring. The differential output optical signal is expressed as:

[0128] I diff(t) = T N I out (12);

[0129] Among them, I diff (t) is the differential output optical signal; I out is the intensity modulated optical signal; T N is the power transfer function of the N-cascaded all-pass microring (as shown in Formula 1).

[0130] As an optional implementation, in step S7, the optical signal processed by the micro-ring optical differentiator needs to be converted back to a spatial domain image in order to analyze the differentiation results. First, the differential output optical signal is photodetected and converted back to an electrical signal. Then, the data is sampled and rearranged to restore the two-dimensional edge image I edge (x,y):

[0131] I edge (x,y)=reshape(I diff (t),M,L) (13);

[0132] Through the above process, the reconfigurable cascaded microring optical differentiator was successfully applied to edge extraction in color images. This method utilizes optical differential operations to efficiently extract and enhance image edge information. Further analysis of simulation results will be conducted to explore its performance and optimization directions.

[0133] Use MATLAB simulation software to construct the image edge detection algorithm. The specific algorithm process is as follows: Figure 5 shown.

[0134] Using this algorithm, we first input a color image, and then convert it into a grayscale image as the basis for edge extraction of the entire system. The input image is as follows: Figure 6 As shown in (a) in the figure, the grayscale image is as follows Figure 6 As shown in (b) in .

[0135] After obtaining the grayscale image, the two-dimensional pixels are converted into a one-dimensional time series, and the one-dimensional time series is converted into an analog signal through DAC, such as Figure 7 As shown. Among them, Figure 7 (a) in the figure represents the analog signal after conversion. Figure 7 (b) in the figure shows a partial display of the analog signal.

[0136] After being converted into an analog signal, the signal is modulated by MZM according to formula (11). The modulated signal is as follows: Figure 8 As shown. Among them, Figure 8 (a) in the figure represents the MZM modulation signal. Figure 8 (b) in the figure shows a partial display of the modulation signal.

[0137] The MZM modulated signal is input into the microring optical differentiator. First, a single microring without GST-SL6 is used for simulation. The optical output signal after entering the microring is as follows: Figure 9 As shown. Among them, Figure 9 (a) in the equation represents the differential output signal. Figure 9 (b) in the figure shows a partial display of the output signal.

[0138] The above process uses the ideal differential amplitude response to replace the micro-ring to process the MZM modulated signal. Figure 9 The differential output signal (a) and the ideal differential output signal are both restored to two-dimensional images, and the results are as follows Figure 10 As shown. Among them, Figure 10 (a) in the figure represents the image processed by the ideal differential process of order 0.98. Figure 10 (b) in the figure shows the image processed by single micro-ring differentiation.

[0139] The differential order of a single microring with respect to the input signal is approximately 0.98. Experimental results show that the edge details extracted from the signal after microring differentiation are highly consistent with the ideal differential result, the overall structure is well preserved, and the edge features are more distinct. Compared with traditional numerical differentiation methods, the microring optical differentiator can more effectively enhance image edge information, improve signal contrast, and make the target outline more distinct. The experimental results fully verify the feasibility and superiority of edge detection technology based on microring optical differentiators.

[0140] After verifying the edge extraction effect of single micro-ring on input image, we use Figure 1 The multi-input cascade micro-ring structure optical differentiator shown in FIG. 1 also uses 1.96 and 2.94 order ideal differentials to extract the edge of the image according to the single micro-ring verification method. The results are shown in FIG. Figure 11 As shown. Among them, Figure 11 (a) in the figure represents the image processed by the ideal differential process of order 1.96. Figure 11 (b) in the figure shows the double micro-ring differential processing image. Figure 11 (c) in the figure represents the 2.94th order ideal differential processing image. Figure 11 (d) in the figure shows the image processed by three micro-rings differentiation.

[0141] Experimental results show that multi-order differentiation introduces a certain degree of image blurring after processing the modulated signal, and the higher the differentiation order, the more pronounced the blurring. This is because high-order differentiation not only enhances the edge information of the image, but also produces a stronger response to high-frequency noise, leading to over-expansion of edge regions and blurred details. The multi-order differentiation achieved by cascading microrings achieves a processing effect highly consistent with the ideal differentiation result, accurately extracting target edges while maintaining good edge sharpness at higher orders. The experimental results further demonstrate that edge detection technology based on reconfigurable microring optical differentiators has broad application prospects in signal processing, image analysis, and optical computing.

[0142] In order to further study the effect of reconfigurable cascade microring optical differentiator on image edge detection, GST-SL6 phase change material is introduced into the cascade microring structure, and the differential order of the microring is adjusted by regulating its loss state. Figure 12 As shown. Among them, Figure 12 (a) in the figure represents the differential processing image of the undercoupled state. Figure 12 (b) in the figure shows the differential processing image of the critical coupling state. Figure 12 (c) in the figure represents the image processed by differential processing in the overcoupled state. The results show that under different GST-SL6 loss states, the microring differentiator is in different states and therefore has different effects on image edge extraction. As the state changes, the reconfigurable differentiator can dynamically adjust the clarity of edge information, achieving continuous control from sharp edge enhancement to edge blurring. Compared with the microring structure with fixed parameters, the reconfigurable differentiator based on GST-SL6 can optimize the presentation of edge details at different differential orders, thereby adaptively adjusting the degree of edge blur in different application scenarios. This result further verifies the advantages of the reconfigurable cascade microring optical differentiator in image processing and provides new possibilities for intelligent optical computing and tunable edge detection.

[0143] The present application is further introduced below using a reconfigurable three-cascade microring optical differentiator.

[0144] like Figure 13 As shown, it has the following key points:

[0145] 1. Design of multi-input controllable cascade microring structure.

[0146] (1) Construct a structural unit consisting of three microrings in cascade, where each microring is physically connected in series but independent of each other in input.

[0147] (2) Unlike the traditional structure that limits the optical input to the link starting port, this application cancels the unified input port and instead sets a separate input port (I1, I2, I3) for each micro-ring, and shares one output port.

[0148] (3) Utilize a multi-input structure to achieve selective activation or combined control of differential functions of different orders.

[0149] 2. Full coverage and zoning control of phase change materials.

[0150] (1) Reversible phase change material is deposited on each microring, and programmable state switching is achieved through electrical / thermal / photocontrol.

[0151] (2) The deposition areas of the materials can be different to enhance the independent regulation properties of different microrings.

[0152] (3) The material state affects the resonance conditions and loss characteristics of the microring, thereby achieving the construction or closure of different differential responses in the frequency domain.

[0153] 3. Unify the output port to realize functional superposition differential output.

[0154] (1) All input signals are ultimately output from a common output port. Different input ports can activate the first-order, second-order, or third-order differential functions respectively and achieve fractional-order differential by adjusting the material state.

[0155] (2) Through the control of the input path and the coordinated regulation of the material state, programmable combination and switching of optical differential operations can be achieved.

[0156] (3) It supports the use of any input port (such as I1) alone to achieve a certain order of differential output, or multiple ports are activated concurrently to achieve a compound differential response.

[0157] The core content of this embodiment is as follows:

[0158] 1. Setting method of independent input ports in the three micro-ring cascade structure.

[0159] (1) Each micro-ring has an independent optical input channel, which is different from the traditional series input.

[0160] (2) The optical signal is only input into the corresponding micro-ring and does not penetrate the previous stage loop.

[0161] (3) By adjusting the material state, the three ports can realize a differential calculation path with adjustable differential order.

[0162] 2. Differential multiplexing structure with shared output ports.

[0163] (1) The output optical signals of the three microrings are converged to a common output port through a coupling structure.

[0164] (2) Realize unified reading of different differential results, facilitating downstream processing and packaging integration.

[0165] (3) The “differential function selector” function can be realized, and the differential operator can be selected through port control.

[0166] 3. Dynamic control and combination mechanism of differential operators.

[0167] (1) Each input port activates an optical differential response of different order.

[0168] (2) Multiple ports can be activated concurrently or selectively individually to achieve any order of combined differential output;

[0169] (3) Support real-time switching, reconstruction and reuse.

[0170] 4. Programmable edge detection capabilities for image processing applications.

[0171] (1) This structure supports differential processing of image signals in the optical domain. By regulating the material state of each microring, differential responses of different orders can be achieved, thereby performing edge extraction at different depths for image grayscale changes.

[0172] (2) Users can adjust the activation state of each input port and the material response state, and combine and output different differential orders as needed to achieve multi-scale and multi-dimensional edge detection functions in image processing.

[0173] (3) This adjustable edge processing mechanism is particularly suitable for scenarios with high edge layer requirements, such as machine vision, surface defect detection, and medical image analysis, and improves the accuracy and adaptability of the system's image understanding.

[0174] Compared with the prior art, the advantages of this application are as follows:

[0175] 1. Original three-input programmable structure.

[0176] Existing optical differentiators typically use a single input port, with signals pre-coupled and transmitted within a series of microrings. However, this application establishes independent input ports I1–I3 for each of the three cascaded microrings. By depositing tunable materials, the device possesses selectable, programmable, and combinable fractional-order differential functionality. This structure, previously unseen in programmable photonic devices such as field-programmable ring arrays, fills a structural gap in differential control.

[0177] 2. Material-level zoning control enhances flexibility.

[0178] This application designs material-controllable regions within each microring, independently controlling the response characteristics of different microrings through state switching, supporting multi-port, multi-order joint regulation. This partitioned control approach enhances the device's functional reconfiguration freedom and response speed, effectively overcoming the limitations of traditional monolithic material control, which suffers from slow response and single functionality.

[0179] 3. Single-ended unified output realizes signal multiplexing.

[0180] The outputs of the three micro-rings are unified and converged to a common output port, simplifying the optical path design and signal processing interface. Compared with the structure used in scientific research to read out the results of different-order differentials using multiple ports, the design of the present invention has greater system integration efficiency and implementation potential, and is suitable for industrial-grade packaging.

[0181] 4.Support high-order differential functions and combinatorial computing capabilities.

[0182] Through innovations in structure and input design, this application can support first-order, second-order, third-order, and fractional-order differential functions, and through simultaneous activation of multiple input terminals, realize order superposition or combination operations, providing richer and more customizable differential operator outputs for complex signal processing.

[0183] 5. Significantly improve system compactness and integration friendliness.

[0184] The entire device structure is designed based on a silicon-based optical waveguide platform, is compatible with mainstream photonic chip processes, has a compact structure and high integration, does not require external driving circuits or large-volume control modules, and is particularly suitable for large-scale photonic computing and edge intelligent systems.

[0185] 6. Programmable edge extraction capabilities for image processing.

[0186] This application dynamically implements the invocation and switching of different differential operators by regulating the combination of material states and input ports, thereby achieving multi-scale, adjustable-intensity edge extraction in image processing. This structure supports flexible control of image response characteristics and is applicable to a variety of image recognition, detection, and visual perception scenarios, improving edge processing accuracy and system adaptability.

[0187] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0188] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A multi-input cascaded micro-ring structure optical differentiator, characterized in that: The multi-input cascade micro-ring structure optical differentiator comprises: Several microring resonators connected in series; Each of the microring resonators is provided with an independent input port, and a plurality of microring resonators connected in series share an output port; different input ports are used to respectively activate optical differential responses of corresponding orders; A reversible phase change material is deposited on each of the microring resonators; the reversible phase change material is used to realize programmable state switching.

2. The multi-input cascaded micro-ring structure optical differentiator according to claim 1, characterized in that: The deposition area of ​​the reversible phase change material is the inner side of the microring resonator.

3. An application method of a multi-input cascaded micro-ring structure optical differentiator, characterized in that: The application method of the multi-input cascade micro-ring structure optical differentiator includes: Convert the input color image to a grayscale image; performing binarization processing on the grayscale image to obtain a binarized image; Performing time series signal conversion on the binarized image to obtain a one-dimensional time series; Performing analog signal conversion on the one-dimensional time series to obtain an analog electrical signal; Performing optical signal modulation conversion on the analog electrical signal to obtain an intensity modulated optical signal; Inputting the intensity modulated optical signal into a multi-input cascaded phase-change microring structure optical differentiator for differentiation to obtain a differential output optical signal; the multi-input cascaded phase-change microring structure optical differentiator is the optical differentiator according to claim 1 or 2; The differential output optical signal is photoelectrically detected to obtain a converted electrical signal, and the converted electrical signal is sampled and data is rearranged to obtain a two-dimensional edge image.

4. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The calculation formula of the grayscale image is: I gray (X,y)=0.299R(x,y)+0.587G(x,y)+0.114B(x,y); Among them, I gray (x,y) is a grayscale image; R(x,y) is the intensity of the red component of the image at the pixel coordinate (x,y); G(x,y) is the intensity of the green component of the image at the pixel coordinate (x,y); B(x,y) is the intensity of the blue component of the image at the pixel coordinate (x,y).

5. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The expression of the binarization process is: Among them, I binary (x, y) is the image after binarization processing; I gray (x,y) is a grayscale image; K is a fixed threshold.

6. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The expression for the time series signal conversion is: S(t)={I binary (x1,y1),I binary (x2,y2),...,I binary (x M ,y L )}; Where S(t) is the pixel value sequence obtained by scanning row by row; M and L are the number of rows and columns of the image respectively; I binary (x M ,y L ) is the image after binarization processing in the Mth row and Lth column.

7. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The expression of analog signal conversion is: Among them, V analog (t) is the analog electrical signal; S(t) is the pixel value sequence obtained by scanning line by line; V max is the maximum voltage of the analog signal.

8. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The expression of the optical signal modulation conversion is: Among them, I out is the intensity modulated optical signal; I in is the input light intensity; V π The voltage required to achieve π phase shift; V analog (t) is the analog electrical signal.

9. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The differential expression is: I diff (t)=T N ·I out ; Among them, I diff (t) is the differential output optical signal; I out is the intensity modulated optical signal; T N is the power transfer function of N-cascaded all-pass micro-rings; a is the loop loss coefficient; t is the transmission coefficient; is the ring phase shift of the microring resonator, which indicates the phase change of the light field when it propagates in the ring; T is the power of the microring resonator; N is the number of microring resonators.

10. The application method of the multi-input cascaded micro-ring structure optical differentiator according to claim 3, characterized in that: The expression for obtaining the two-dimensional edge image is: I edge (x,y)=reshape(I diff (t),M,L); Among them, I edge (x,y) is a two-dimensional edge image; I diff (t) is the differential output light signal; M and L are the number of rows and columns of the image, respectively.

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